000 | 03270nam a22005055i 4500 | ||
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001 | 978-3-319-13212-9 | ||
003 | DE-He213 | ||
005 | 20200421112544.0 | ||
007 | cr nn 008mamaa | ||
008 | 141227s2015 gw | s |||| 0|eng d | ||
020 |
_a9783319132129 _9978-3-319-13212-9 |
||
024 | 7 |
_a10.1007/978-3-319-13212-9 _2doi |
|
050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aCOM004000 _2bisacsh |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aAdhikari, Animesh. _eauthor. |
|
245 | 1 | 0 |
_aAdvances in Knowledge Discovery in Databases _h[electronic resource] / _cby Animesh Adhikari, Jhimli Adhikari. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2015. |
|
300 |
_aXV, 370 p. 136 illus. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aIntelligent Systems Reference Library, _x1868-4394 ; _v79 |
|
505 | 0 | _aIntroduction -- Synthesizing conditional patterns in a database -- Synthesizing arbitrary Boolean expressions induced by frequent itemsets -- Measuring association among items in a database -- Mining association rules induced by item and quantity purchased -- Mining patterns different related databases -- Mining icebergs in different time-stamped data sources.-Synthesizing exceptional patterns in different data Sources -- Clustering items in time-stamped databases -- Synthesizing some extreme association rules from multiple databases -- Clustering local frequency items in multiple data sources -- Mining patterns of select items in different data sources -- Mining calendar-based periodic patterns in time-stamped data -- Measuring influence of an item in time-stamped databases -- Clustering multiple databases induced by local patterns -- Enhancing quality of patterns in multiple related databases -- Concluding remarks. | |
520 | _aThis book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases. Various interesting and intelligent algorithms are reported on data mining tasks. A large number of association measures are presented, which play significant roles in decision support applications. This book presents, discusses and contrasts new developments in mining time-stamped data, time-based data analyses, the identification of temporal patterns, the mining of multiple related databases, as well as local patterns analysis. . | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aData mining. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
700 | 1 |
_aAdhikari, Jhimli. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319132112 |
830 | 0 |
_aIntelligent Systems Reference Library, _x1868-4394 ; _v79 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-13212-9 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c58439 _d58439 |